Integrating statistical and mechanistic approaches with biotic and environmental variables improves model predictions of the impact of climate and land-use changes on future mosquito-vector abundance, diversity and distributions in Australia.
Eugene T Madzokere, Willow Hallgren, Oz Sahin, Julie A Webster, Cameron E Webb, Brendan Mackey, Lara J Herrero
Author Information
Eugene T Madzokere: Institute for Glycomics, Griffith University, Gold Coast Campus, Southport, QLD, 4215, Australia.
Willow Hallgren: Environmental Futures Research Institute, Griffith School of Environment, Gold Coast campus, Griffith University, Gold Coast, QLD, 4222, Australia.
Oz Sahin: Cities Research Institute, Gold Coast campus, Griffith University, Gold Coast, QLD, 4222, Australia.
Julie A Webster: QIMR Berghofer Medical Research Institute, 300 Herston Road, Herston, QLD, 4006, Australia.
Cameron E Webb: Department of Medical Entomology, NSW Health Pathology, ICPMR, Westmead Hospital, Westmead, NSW, 2145, Australia.
Changes to Australia's climate and land-use patterns could result in expanded spatial and temporal distributions of endemic mosquito vectors including Aedes and Culex species that transmit medically important arboviruses. Climate and land-use changes greatly influence the suitability of habitats for mosquitoes and their behaviors such as mating, feeding and oviposition. Changes in these behaviors in turn determine future species-specific mosquito diversity, distribution and abundance. In this review, we discuss climate and land-use change factors that influence shifts in mosquito distribution ranges. We also discuss the predictive and epidemiological merits of incorporating these factors into a novel integrated statistical (SSDM) and mechanistic species distribution modelling (MSDM) framework. One potentially significant merit of integrated modelling is an improvement in the future surveillance and control of medically relevant endemic mosquito vectors such as Aedes vigilax and Culex annulirostris, implicated in the transmission of many arboviruses such as Ross River virus and Barmah Forest virus, and exotic mosquito vectors such as Aedes aegypti and Aedes albopictus. We conducted a focused literature search to explore the merits of integrating SSDMs and MSDMs with biotic and environmental variables to better predict the future range of endemic mosquito vectors. We show that an integrated framework utilising both SSDMs and MSDMs can improve future mosquito-vector species distribution projections in Australia. We recommend consideration of climate and environmental change projections in the process of developing land-use plans as this directly impacts mosquito-vector distribution and larvae abundance. We also urge laboratory, field-based researchers and modellers to combine these modelling approaches. Having many different variations of integrated (SDM) modelling frameworks could help to enhance the management of endemic mosquitoes in Australia. Enhanced mosquito management measures could in turn lead to lower arbovirus spread and disease notification rates.
